class_docstr: SageMaker ``MultiDataModel`` can be used to deploy multiple models to the same ``Endpoint``.
  
  And also deploy additional models to an existing SageMaker multi-model ``Endpoint``
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docstr: Return a container definition set.
  
  Definition set includes MultiModel mode, model data and other parameters
  from the model (if available).
  
  Subclasses can override this to provide custom container definitions
  for deployment to a specific instance type. Called by ``deploy()``.
  
  Returns:
      dict[str, str]: A complete container definition object usable with the CreateModel API
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code: def prepare_container_def(
      self,
      instance_type=None,
      accelerator_type=None,
      serverless_inference_config=None,
      accept_eula=None,
  ):
      """Return a container definition set.
  
      Definition set includes MultiModel mode, model data and other parameters
      from the model (if available).
  
      Subclasses can override this to provide custom container definitions
      for deployment to a specific instance type. Called by ``deploy()``.
  
      Returns:
          dict[str, str]: A complete container definition object usable with the CreateModel API
      """
      # Copy the trained model's image URI and environment variables if they exist. Models trained
      # with FrameworkEstimator set framework specific environment variables which need to be
      # copied over
      if self.model:
          container_definition = self.model.prepare_container_def(
              instance_type, accelerator_type
          )
          image_uri = container_definition["Image"]
          environment = container_definition["Environment"]
      else:
          image_uri = self.image_uri
          environment = self.env
      return sagemaker.container_def(
          image_uri,
          env=environment,
          model_data_url=self.model_data_prefix,
          container_mode=self.container_mode,
          accept_eula=accept_eula,
      )
  
file_path: sagemaker-python-sdk/src/sagemaker/multidatamodel.py
imports: from __future__ import absolute_import
  import os
  from typing import Union, Optional
  from six.moves.urllib.parse import urlparse
  import sagemaker
  from sagemaker import local, s3
  from sagemaker.deprecations import removed_kwargs
  from sagemaker.model import Model
  from sagemaker.session import Session
  from sagemaker.utils import pop_out_unused_kwarg, format_tags
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 2 for calling the MultiDataModel obj's underlying member method code with example usage: obj.prepare_container_def(instance_type, accelerator_type, serverless_inference_config, accept_eula) and returns: sagemaker